caa a22 4500 606162755 CHVBK 20210128100640.0 cr unu---uuuuu 210128e20150201xx s 000 0 eng 10.1007/s11062-015-9489-y doi (NATIONALLICENCE)springer-10.1007/s11062-015-9489-y Dynamic Properties of Purkinje Cells Having Different Electrophysiological Parameters: a Model Study [Elektronische Daten] [X. Zhang, S. Liu, H. Ren, Y. Wen, Y. Zeng] Simple spikes and complex spikes are two distinguishing features in neurons of the cerebellar cortex; the motor learning and memory processes are dependent on these firing patterns. In our research, the detailed firing behaviors of Purkinje cells were investigated using a computer compartmental neuronal model. By means of application of numerical stimuli, the abundant dynamical properties involved in the multifarious firing patterns (such as the Max-Min potentials of each spike and period-adding/perioddoubling bifurcations) appeared. Neuronal interspike interval (ISI) diagrams, frequency diagrams, and current-voltage diagrams for different ions were plotted. Finally, Poincaré mapping was used as a theoretical method to markedly distinguish timing of the above firing patterns. Our simulation results indicated that firing of Purkinje cells varies dynamically depending on different electrophysiological parameters of these neurons, and the respective properties may play significant roles in the formation of the mentioned characteristics of dynamical firings in the coding strategy for information processing and learning. Springer Science+Business Media New York, 2015 Purkinje cell nationallicence computer compartmental model nationallicence Max-Min potential nationallicence interspike intervals (ISIs) nationallicence current-voltage diagram nationallicence frequency nationallicence Poincaré mapping nationallicence Zhang X. Department of Mathematics, South China University of Technology, Guangzhou, China aut Liu S. Department of Mathematics, South China University of Technology, Guangzhou, China aut Ren H. Department of Mathematics, South China University of Technology, Guangzhou, China aut Wen Y. Department of Mathematics, South China University of Technology, Guangzhou, China aut Zeng Y. Biomedical Engineering Center, Beijing University of Technology, Beijing, China aut Neurophysiology Springer US; http://www.springer-ny.com 47/1(2015-02-01), 2-10 0090-2977 47:1<2 2015 47 11062 https://doi.org/10.1007/s11062-015-9489-y text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s11062-015-9489-y text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Zhang X. Department of Mathematics, South China University of Technology, Guangzhou, China aut NATIONALLICENCE 700 1- Liu S. Department of Mathematics, South China University of Technology, Guangzhou, China aut NATIONALLICENCE 700 1- Ren H. Department of Mathematics, South China University of Technology, Guangzhou, China aut NATIONALLICENCE 700 1- Wen Y. Department of Mathematics, South China University of Technology, Guangzhou, China aut NATIONALLICENCE 700 1- Zeng Y. Biomedical Engineering Center, Beijing University of Technology, Beijing, China aut NATIONALLICENCE 773 0- Neurophysiology Springer US; http://www.springer-ny.com 47/1(2015-02-01), 2-10 0090-2977 47:1<2 2015 47 11062